黄土高原生态系统碳储量情景模拟与驱动因素——基于PLUS–InVEST-Geodector模型的研究

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摘要以我国重要生态屏障黄土高原为案例地,借助PLUS模型预测2030年不同发展情景下的土地利用格局,运用InVEST-Geodector模型对生态系统碳储量时空变化及驱动因素展开分析,研究结果表明:(1)自然增长与生态保护情景下耕地面积将减少,耕地保护情景下草地面积大幅减少,林地与水域在三种情景下均得到了有效保护.(2)自然发展、生态保护、耕地保护情景下生态系统碳储量分别为4.922,5.021,4.922Pg;相比2020年分别增加8.07,37.22,8.07Tg.碳储量具有明显的空间异质性,秦岭北麓、太行山、吕梁山等区域碳密度高,鄂尔多斯市及其周边区域碳密度低.地类数量变化与地类转换对碳储量增减变化有重要影响.综合来看,生态保护情景更符合研究区未来发展需求.(3)坡度与降水是影响生态系统碳储量的核心因素,坡度、土壤类型或年均气温与其他因素的交互作用是驱动碳储量区域差异及变化的主导因素组合.

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	刘康
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关键词 ：生态系统碳储量, 情景模拟, 驱动因素, PLUS-InVEST模型, 地理探测器, 黄土高原

Abstract：We used the PLUS model to predict the land use pattern under different development scenarios in 2030 in the Loess Plateau, an important ecological barrier in China, and applied the InVEST-Geodector model to analyze the spatiotemporal changes and driving factors in ecosystem carbon storage from 2020 to 2030. The findings were as follows: (1) The area of cropland will decrease under the natural development and ecological protection scenarios; the area of grassland decreases significantly under the cropland protection scenario, and forests and waters are effectively protected under all three scenarios. (2) The ecosystem carbon storage under the natural development, ecological protection, and cropland protection scenarios is 4.922, 5.021, and 4.922Pg, respectively. Compared with those in 2020, carbon storage will increase by 8.07, 37.22, and 8.07Tg, respectively. Carbon storage has obvious spatial heterogeneity, with high carbon density in the northern Qinling Mountains, Taihang Mountains, and Lvliang Mountains and low carbon density in Erdos City and its surrounding areas. Changes in carbon storage are closely related to the changes in the number of land classes and conversion of land use types. In conclusion, the ecological protection scenario is more in line with the future development needs of the study area. (3) The core determinants of ecosystem carbon storage are slope and precipitation, and the dominating combinations of factors driving regional differences and changes in carbon storage are the interactions of slope, soil type, or average annual temperature content with other variables.

Key words： ecosystem carbon storage scenario simulation driving factors PLUS-InVEST-Geodector model the Loess Plateau

收稿日期: 2024-10-08

PACS:

X171.1

基金资助:国家社科基金重大项目(24&ZD108)

作者简介: 刘康(1995–),男,陕西安康人,博士研究生,从事土地高效低碳利用研究.发表论文10余篇.kangl9511@163.com.

引用本文:

刘康, 张寒, 张道军, 郑伟伟, 张超正. 黄土高原生态系统碳储量情景模拟与驱动因素——基于PLUS–InVEST-Geodector模型的研究[J]. 中国环境科学, 2025, 45(4): 2159-2170. LIU Kang, ZHANG Han, ZHANG Dao-jun, ZHENG Wei-wei, ZHANG Chao-zheng. Scenario simulation and driving factors of ecosystem carbon storage in the Loess Plateau: A study based on the PLUS-InVEST-Geodector model. CHINA ENVIRONMENTAL SCIENCECE, 2025, 45(4): 2159-2170.

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http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2025/V45/I4/2159

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